Hybrid stochastic local unit roots

Two approaches have dominated formulations designed to capture small departures from unit root autoregressions. The first involves deterministic departures that include local-to-unity (LUR) and mildly (or moderately) integrated (MI) specifications where departures shrink to zero as the sample size n...

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Main Authors: LIEBERMAN, Offer, PHILLIPS, Peter C. B.
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Language:English
Published: Institutional Knowledge at Singapore Management University 2020
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Online Access:https://ink.library.smu.edu.sg/soe_research/2385
https://ink.library.smu.edu.sg/context/soe_research/article/3384/viewcontent/Hybrid_stochastic_local_unit_roots_sv.pdf
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spelling sg-smu-ink.soe_research-33842020-05-28T06:59:19Z Hybrid stochastic local unit roots LIEBERMAN, Offer PHILLIPS, Peter C. B. Two approaches have dominated formulations designed to capture small departures from unit root autoregressions. The first involves deterministic departures that include local-to-unity (LUR) and mildly (or moderately) integrated (MI) specifications where departures shrink to zero as the sample size n -> infinity. The second approach allows for stochastic departures from unity, leading to stochastic unit root (STUR) specifications. This paper introduces a hybrid local stochastic unit root (LSTUR) specification that has both LUR and STUR components and allows for endogeneity in the time varying coefficient that introduces structural elements to the autoregression. This hybrid model generates trajectories that, upon normalization, have non-linear diffusion limit processes that link closely to models that have been studied in mathematical finance, particularly with respect to option pricing. It is shown that some LSTUR parameterizations have a mean and variance which are the same as a random walk process but with a kurtosis exceeding 3, a feature which is consistent with much financial data. We develop limit theory and asymptotic expansions for the process and document how inference in LUR and STUR autoregressions is affected asymptotically by ignoring one or the other component in the more general hybrid generating mechanism. In particular, we show how confidence belts constructed from the LUR model are affected by the presence of a STUR component in the generating mechanism. The import of these findings for empirical research is explored in an application to the spreads on US investment grade corporate debt. 2020-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/2385 info:doi/10.1016/j.jeconom.2019.05.023 https://ink.library.smu.edu.sg/context/soe_research/article/3384/viewcontent/Hybrid_stochastic_local_unit_roots_sv.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Autoregression Local unit root Nonlinear diffusion Stochastic unit root Time-varying coefficient Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Autoregression
Local unit root
Nonlinear diffusion
Stochastic unit root
Time-varying coefficient
Econometrics
spellingShingle Autoregression
Local unit root
Nonlinear diffusion
Stochastic unit root
Time-varying coefficient
Econometrics
LIEBERMAN, Offer
PHILLIPS, Peter C. B.
Hybrid stochastic local unit roots
description Two approaches have dominated formulations designed to capture small departures from unit root autoregressions. The first involves deterministic departures that include local-to-unity (LUR) and mildly (or moderately) integrated (MI) specifications where departures shrink to zero as the sample size n -> infinity. The second approach allows for stochastic departures from unity, leading to stochastic unit root (STUR) specifications. This paper introduces a hybrid local stochastic unit root (LSTUR) specification that has both LUR and STUR components and allows for endogeneity in the time varying coefficient that introduces structural elements to the autoregression. This hybrid model generates trajectories that, upon normalization, have non-linear diffusion limit processes that link closely to models that have been studied in mathematical finance, particularly with respect to option pricing. It is shown that some LSTUR parameterizations have a mean and variance which are the same as a random walk process but with a kurtosis exceeding 3, a feature which is consistent with much financial data. We develop limit theory and asymptotic expansions for the process and document how inference in LUR and STUR autoregressions is affected asymptotically by ignoring one or the other component in the more general hybrid generating mechanism. In particular, we show how confidence belts constructed from the LUR model are affected by the presence of a STUR component in the generating mechanism. The import of these findings for empirical research is explored in an application to the spreads on US investment grade corporate debt.
format text
author LIEBERMAN, Offer
PHILLIPS, Peter C. B.
author_facet LIEBERMAN, Offer
PHILLIPS, Peter C. B.
author_sort LIEBERMAN, Offer
title Hybrid stochastic local unit roots
title_short Hybrid stochastic local unit roots
title_full Hybrid stochastic local unit roots
title_fullStr Hybrid stochastic local unit roots
title_full_unstemmed Hybrid stochastic local unit roots
title_sort hybrid stochastic local unit roots
publisher Institutional Knowledge at Singapore Management University
publishDate 2020
url https://ink.library.smu.edu.sg/soe_research/2385
https://ink.library.smu.edu.sg/context/soe_research/article/3384/viewcontent/Hybrid_stochastic_local_unit_roots_sv.pdf
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